Transfusion of red blood cells (RBCs), the most common therapeutic procedure performed in US hospitals, is usually effective at preventing morbidity and mortality in anemic patients. However, recent studies indicate that some RBC units have functional defects that impair their efficacy and may actually cause harm to transfused patients. These defects, which appear to increase the longer RBC units are stored prior to transfusion, have been called RBC storage lesions. Transfusion of RBC units with storage lesions may adversely affect thousands of patients annually, but at present we have no accurate methods to identify such units. During the previous funding period for this R01 grant, we observed unexpected donor-to-donor variability in RBC metabolism during blood bank storage. Based on these data, we propose to identify specific metabolic (human RBCs) and genetic (murine RBCs) biomarkers that not only reflect the underlying differences in RBC function due to storage time and/or donor factors, but also can be used clinically to predict which RBC units may cause adverse post-transfusion events, allowing them to be removed from the blood supply before transfusion. To provide the most powerful approach to achieve this goal, we propose an integrated research effort that combines (1) the relevancy of donor/recipient-based human RBC transfusion investigations, with (2) the mechanistic power of mouse models. The human studies will utilize methodologies we have developed to identify metabolic biomarkers that predict RBC function, post-transfusion RBC survival, and vascular effects. The advantages of mouse studies include finely characterized genetics, rapid breeding times, ease of generating complex pedigrees, and the power of phenotype-genotype analysis. These advantages will be exploited by performing GWAS to identify genetic markers for mouse RBC storage phenotypes, and then selectively backcrossing to establish causality between selected genetic elements and phenotypes of interest. The proposed coordinated investigations allow each model to be used for its unique strengths, while compensating for intrinsic weaknesses, and thus provides efficient cross- validation of selected biomarkers. These studies will extend work started during the previous funding period, and will lead to the validation of RBC biomarkers that we believe will identify RBC units most likely to cause adverse recipient effects, allowing them to be sequestered prior to transfusion.